Clustering Motivational Profiles: How Perceived Value, Cost, and Self-Efficacy Shape Students’ Regulatory Strategies

This study investigates the interplay between university students’ motivational beliefs and their regulatory strategies when facing challenging academic tasks. Drawing on the Expectancy–Value–Cost (EVC) model, the research characterizes distinct motivational profiles based on perceived self-efficacy, task value, and perceived cost. A quantitative study was conducted with a sample of 1184 Chilean university students across various disciplines, including Engineering, Health Sciences, and Social Sciences. Participants identified a recent challenging task and completed a battery of validated instruments, including the Brief Regulation of Motivation Scale (BroMS) and scales for perceived cost, self-efficacy, and task value. Using Machine Learning techniques, specifically the Fuzzy C-Means (FCM) algorithm, the analysis identified four distinct student profiles (Agentic Mindset, Alienated Mindset, Paralyzed Mindset, Growth Mindset). These clusters were evaluated based on statistical indices (R 2 , AIC, BIC, and Silhouette) and theoretical coherence. Subsequent ANOVA and post hoc analyses (Holm correction) revealed significant differences among these profiles in their reported levels of motivational regulation and willpower. The findings suggest that students with high self-efficacy and task value combined with manageable perceived costs employ more effective motivational regulation strategies. Conversely, profiles characterized by high perceived cost and low self-efficacy show diminished regulatory capacity. This research contributes to understanding how personal and task-related perceptions interact to shape volitional control in demanding academic environments, offering insights for targeted interventions to support academic persistence and success.